Imaging-Based Molecular Characterization of Adult-Type Diffuse Glioma Using Diffusion and Perfusion MRI in Pre- and Post-Treatment Stage Considering Spatial and Temporal Heterogeneity

被引:0
|
作者
Roh, Yun Hwa [1 ]
Cheong, E-Nae [2 ,3 ]
Park, Ji Eun [2 ,3 ]
Choi, Yangsean [2 ,3 ]
Jung, Seung Chai [2 ,3 ]
Song, Sang Woo [4 ]
Kim, Young-Hoon [4 ]
Hong, Chang-Ki [4 ]
Kim, Jeong Hoon [4 ]
Kim, Ho Sung [2 ,3 ]
机构
[1] Sungkyunkwan Univ, Samsung Med Ctr, Sch Med, Dept Radiol, Seoul, South Korea
[2] Univ Ulsan, Coll Med, Dept Radiol, Seoul, South Korea
[3] Univ Ulsan, Res Inst Radiol, Asan Med Ctr, Coll Med, Seoul, South Korea
[4] Univ Ulsan, Asan Med Ctr, Coll Med, Dept Neurosurg, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
characterization; EGFR; glioma; heterogeneity; IDH; GLIOBLASTOMA; CLASSIFICATION; AMPLIFICATION; COEFFICIENT; EXPRESSION; PREDICTION; EGFRVIII; SYSTEM; IMPACT;
D O I
10.1002/jmri.29781
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
BackgroundImaging-based molecular characterization is important for identifying treatment targets in adult-type diffuse gliomas.PurposeTo assess isocitrate dehydrogenase (IDH) mutation and epidermal growth factor receptor (EGFR) amplification status in primary and recurrent gliomas using diffusion and perfusion MRI, addressing spatial and temporal heterogeneity.Study TypeRetrospective.SubjectsThree-hundred and twelve newly diagnosed (cross-sectional set, 57.9 +/- 13.2 years, 52.2% male, 235 IDH-wildtype, 71 EGFR-amplified) and 38 recurrent (longitudinal set, 53.1 +/- 13.4 years, 44.7% male, 30 IDH-wildtype, 13 EGFR-amplified) adult-type diffuse glioma patients.Field Strength/Sequence3.0T; diffusion weighted and dynamic susceptibility contrast-perfusion weighted imaging.AssessmentRadiomics features from contrast-enhancing tumors (CET) and non-enhancing lesions (NEL) were extracted from apparent diffusion coefficient and perfusion maps. Spatial heterogeneity was assessed using intersection and Bhattacharyya distance between CET and NEL. Stable imaging features were identified in patients with unchanged genetic profiles in the longitudinal set. The "best model," using features from the cross-sectional set (n = 312), and the "concordant model," using stable features identified in the longitudinal set (n = 38), were constructed using the LASSO for IDH and EGFR status.Statistical TestsThe area under the receiver-operating-characteristic curve (AUC).ResultsFor IDH mutations, both best and concordant models demonstrated high AUCs in the cross-sectional set (0.936; 95% confidence interval [CI]: 0.903-0.969 and 0.964 [0.943-0.986], respectively). Only the concordant model maintained strong performance in recurrent tumors (AUC, 0.919 vs. 0.656). For EGFR amplification in IDH-wildtype, the best and concordant models showed AUCs of 0.821 (95% CI: 0.761-0.881) and 0.746 (95% CI: 0.675-0.817) in newly diagnosed gliomas, but poor performance in recurrent tumors with AUCs of 0.503 (95% CI: 0.34-0.665) and 0.518 (95% CI: 0.357-0.678).Data ConclusionDiffusion and perfusion MRI characterized IDH status in both newly diagnosed and recurrent gliomas, but showed limited diagnostic performance for EGFR, especially for recurrent tumors.Evidence Level3Technical EfficacyStage 3
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页数:12
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